Pinned Repositories
18337
18.337 - Parallel Computing and Scientific Machine Learning
18S191
Course 18.S191 at MIT, fall 2020 - Introduction to computational thinking with Julia:
2018-MachineLearning-Lectures-ESA
Machine Learning Lectures at the European Space Agency (ESA) in 2018
awesome-astrodata
Awesome list for astronomy data and resources for self-learning
BayesianOptimization
Bayesian Optimization with several acquisition functions
deep-learning-tutorial
ETHZ-system-Identification-Exercises
fastai
The fast.ai deep learning library, lessons, and tutorials
gan-tools
GSoC-2018-Work-Report
Google Summer Of Code 2018 Work Report
roshni-kamath's Repositories
roshni-kamath/18337
18.337 - Parallel Computing and Scientific Machine Learning
roshni-kamath/18S191
Course 18.S191 at MIT, fall 2020 - Introduction to computational thinking with Julia:
roshni-kamath/2018-MachineLearning-Lectures-ESA
Machine Learning Lectures at the European Space Agency (ESA) in 2018
roshni-kamath/awesome-astrodata
Awesome list for astronomy data and resources for self-learning
roshni-kamath/BayesianOptimization
Bayesian Optimization with several acquisition functions
roshni-kamath/deep-learning-tutorial
roshni-kamath/ETHZ-system-Identification-Exercises
roshni-kamath/fastai
The fast.ai deep learning library, lessons, and tutorials
roshni-kamath/gan-tools
roshni-kamath/GSoC-2018-Work-Report
Google Summer Of Code 2018 Work Report
roshni-kamath/MachineLearning
A collection of Python code and machine learning exercises
roshni-kamath/MES
Implementation of Max-value Entropy Search. (Using only numpy)
roshni-kamath/minitorch
Minitorch
roshni-kamath/mit_computationalthinking
roshni-kamath/numerical-linear-algebra
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
roshni-kamath/OptML_course
EPFL Course - Optimization for Machine Learning - CS-439
roshni-kamath/programmers-introduction-to-mathematics
Code for A Programmer's Introduction to Mathematics
roshni-kamath/python-machine-learning
roshni-kamath/stat-learning
Notes and exercise attempts for "An Introduction to Statistical Learning"
roshni-kamath/Stochastic-Gradient-Descent
The laboratory from CLOUDS Course at EURECOM
roshni-kamath/StochasticGradientDescent
Simple Notebook to work on SGD, first with a principled introduction, then with serial algorithms, and finally with distributed algorithms using spark